Visualization in Practice

会議の名前
CHI 2023
The Tactile Dimension: A Method for Physicalizing Touch Behaviors
要旨

Traces of touch provide valuable insight into how we interact with the physical world. Measuring touch behavior, however, is expensive and imprecise. Utilizing a fluorescent UV tracer powder, we developed a low-cost analog method to capture persistent, high-contrast touch records on arbitrary objects. We describe our process for selecting a tracer, methods for capturing, enhancing, and aggregating traces, and approaches to examining qualitative aspects of the user experience. Three user studies demonstrate key features of this method. First, we show that it provides clear and durable traces on objects representative of scientific visualization, physicalization, and product design. Second, we demonstrate how this method could be used to study touch perception, by measuring how task and narrative framing elicit different touch behaviors on the same object. Third, we demonstrate how this method can be used to evaluate data physicalizations by observing how participants touch two different physicalizations of COVID-19 time-series data.

受賞
Honorable Mention
著者
Laura J. Perovich
Northeastern University, Boston, Massachusetts, United States
Bernice Rogowitz
Visual Perspectives Research , Westchester, New York, United States
Victoria Crabb
Northeastern University, Boston, Massachusetts, United States
Jack Vogelsang
Northeastern University, Boston, Massachusetts, United States
Sara Hartleben
Northeastern University, Boston, Massachusetts, United States
Dietmar Offenhuber
Northeastern University, Boston, Massachusetts, United States
論文URL

https://doi.org/10.1145/3544548.3581137

動画
Designing Resource Allocation Tools to Promote Fair Allocation: Do Visualization and Information Framing Matter?
要旨

Studies on human decision-making focused on humanitarian aid have found that cognitive biases can hinder the fair allocation of resources. However, few HCI and Information Visualization studies have explored ways to overcome those cognitive biases. This work investigates whether the design of interactive resource allocation tools can help to promote allocation fairness. We specifically study the effect of presentation format (using text or visualization) and a specific framing strategy (showing resources allocated to groups or individuals). In our three crowdsourced experiments, we provided different tool designs to split money between two fictional programs that benefit two distinct communities. Our main finding indicates that individual-framed visualizations and text may be able to curb unfair allocations caused by group-framed designs. This work opens new perspectives that can motivate research on how interactive tools and visualizations can be engineered to combat cognitive biases that lead to inequitable decisions.

著者
Arnav Verma
University of Toronto, Toronto, Ontario, Canada
Luiz Morais
Inria, Bordeaux, France
Pierre Dragicevic
Univ. Bordeaux, CNRS, Inria, LaBRI, Bordeaux, France
Fanny Chevalier
University of Toronto, Toronto, Ontario, Canada
論文URL

https://doi.org/10.1145/3544548.3580739

動画
From Asymptomatics to Zombies: Visualization-Based Education of Disease Modeling
要旨

Throughout the COVID-19 pandemic, visualizations became commonplace in public communications to help people make sense of the world and the reasons behind government-imposed restrictions. Though the adult population were the main target of these messages, children were affected by restrictions through not being able to see friends and virtual schooling. However, through these daily models and visualizations, the pandemic response provided a way for children to understand what data scientists really do and provided new routes for engagement with STEM subjects. In this paper, we describe the development of an interactive and accessible visualization tool to be used in workshops for children to explain computational modeling of diseases, in particular COVID-19. We detail our design decisions based on approaches evidenced to be effective and engaging such as unplugged activities and interactivity. We share reflections and learnings from delivering these workshops to 140 children and assess their effectiveness.

著者
Graham McNeill
University of Warwick, Coventry, United Kingdom
Max Sondag
University of Cologne, Cologne, Germany
Stewart Powell
Technocamps, Swawnsea, United Kingdom
Phoebe Asplin
University of Warwick, Coventry, United Kingdom
Cagatay Turkay
University of Warwick, Coventry, -, United Kingdom
Faron Moller
Swansea University, Swansea, United Kingdom
Daniel Archambault
Swansea University, Swansea, United Kingdom
論文URL

https://doi.org/10.1145/3544548.3581573

動画
iBall: Augmenting Basketball Videos with Gaze-moderated Embedded Visualizations
要旨

We present iBall, a basketball video-watching system that leverages gaze-moderated embedded visualizations to facilitate game understanding and engagement of casual fans. Video broadcasting and online video platforms make watching basketball games increasingly accessible. Yet, for new or casual fans, watching basketball videos is often confusing due to their limited basketball knowledge and the lack of accessible, on-demand information to resolve their confusion. To assist casual fans in watching basketball videos, we compared the game-watching behaviors of casual and die-hard fans in a formative study and developed iBall based on the findings. iBall embeds visualizations into basketball videos using a computer vision pipeline, and automatically adapts the visualizations based on the game context and users’ gaze, helping casual fans appreciate basketball games without being overwhelmed. We confirmed the usefulness, usability, and engagement of iBall in a study with 16 casual fans, and further collected feedback from 8 die-hard fans.

著者
Zhutian Chen
Harvard University, Boston, Massachusetts, United States
Qisen Yang
Zhejiang University, Hangzhou, Zhejiang, China
Jiarui Shan
Harvard University, Cambridge, Massachusetts, United States
Tica Lin
Harvard University, Cambridge, Massachusetts, United States
Johanna Beyer
Harvard University, Cambridge, Massachusetts, United States
Haijun Xia
University of California, San Diego, San Diego, California, United States
Hanspeter Pfister
Harvard University, Cambridge, Massachusetts, United States
論文URL

https://doi.org/10.1145/3544548.3581266

動画
Working with Forensic Practitioners to Understand the Opportunities and Challenges for Mixed-Reality Digital Autopsy
要旨

Forensic practitioners analyse intrinsic 3D data daily on 2D screens. We explore novel immersive visualisation techniques that enable digital autopsy through analysis of 3D imagery. We employ a user-centred design process involving four rounds of user feedback: (1) formative interviews eliciting opportunities and requirements for mixed-reality digital autopsies; (2) a larger workshop identifying our prototype's limitations and further use-cases and interaction ideas; (3+4) two rounds of qualitative user validation of successive prototypes of novel interaction techniques for pathologist sensemaking. Overall, we find MR holds great potential to enable digital autopsy, initially to supplement physical autopsy, but ultimately to replace it. We found that experts were able to use our tool to perform basic virtual autopsy tasks, MR setup promotes exploration and sense making of cause of death, and subject to limitations of current MR technology, the proposed system is a valid option for digital autopsies, according to experts' feedback.

著者
Vahid Pooryousef
Monash University, Melbourne, Australia
Maxime Cordeil
The University of Queensland, Brisbane, Australia
Lonni Besançon
Linköping University, Norrköping, Sweden
Christophe Hurter
Université de Toulouse, Toulouse, France
Tim Dwyer
Monash University, Melbourne, VIC, Australia
Richard Bassed
Monash University, Melbourne, Australia
論文URL

https://doi.org/10.1145/3544548.3580768

動画
How Data Analysts Use a Visualization Grammar in Practice
要旨

Visualization grammars, often based on the Grammar of Graphics (GoG), have much potential for augmenting data analysis in a programming environment. However, we do not know how analysts conceptualize grammar abstractions, or how a visualization grammar works with data analysis in practice. Therefore, we qualitatively analyzed how experienced analysts (N=6) from TidyTuesday, a social data project, wrangled and visualized data using GoG-based ggplot2 without given tasks in R Markdown. Though participants' analysis and customization needs could mismatch with GoG component design, their analysis processes aligned with the goal of GoG to expedite visualization iteration. We also found a feedback loop and tight coupling between visualization and data transformation code, explaining both participants' productivity and their errors. From these results, we discuss how future visualization grammars can become more practical for analysts and how visualization grammar and analysis tools can better integrate within a programming (i.e., computational notebook) environment.

著者
Xiaoying Pu
University of California, Merced, Merced, California, United States
Matthew Kay
Northwestern University, Chicago, Illinois, United States
論文URL

https://doi.org/10.1145/3544548.3580837

動画